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داوران 1399

داوران1400

داوران سال 1401

داوران 1402

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مدل ارزیابی سطح هوش تجاری در سیستم‌های سازمانی

نویسندگان

1 عضو هیات علمی دانشگاه آزاد اسلامی، واحد فیروزکوه

2 دانشجوی دکتری مدیریت فناوری اطلاعات، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبائی

چکیده

      بسیاری از سازمان‌ها که امروزه، سیستم‌های سازمانی مانند سیستم‌های برنامه‌ریزی منابع سازمان (ERP)، سیستم‌های مدیریت زنجیره تامین (SCM) و سیستم‌های مدیریت روابط مشتریان (CRM) را پیاده‌سازی نموده‌اند، هنوز از هوش تجاری در فرایندهای تصمیم‌گیری برخوردار نیستند. مدل‌ها و روش‌های ارزیابی و سنجش هوش تجاری در سیستم‌های سازمانی می‌تواند در تشخیص سطح هوش سیستم‌ها و ایجاد فضای مناسب پشتیبانی تصمیم‌گیری، مفید باشند. در این مقاله در مورد معیارهای ارزیابی هوش تجاری، ساختار و عوامل موثر در مدل ارزیابی هوش تجاری بحث می شود. عوامل و مدل پیشنهادی جهت ارزیابی هوش تجاری ارائه شده در این مقاله، سازمان‌ها را در ارتقاء تصمیم‌گیری یاری می رساند. این تحقیق با مرور جامع ادبیات موضوع، پیمایش و انجام تحلیل عاملی، یک مدل شش عاملی شامل ابعاد "پشتیبانیتصمیمتحلیلیهوشمند"، "یکپارچگیبامحیطوتجربیاتگروهی"، "مدل‌هایتوصیه‌کنندهوبهینه‌کننده"، "دلیلآوری"، "ابزارهایارتقاتصمیم"، و "رضایتذینفعان" جهت ارزیابی هوش تجاری ارائه می‌نماید. این مدل با ارائه معیارها و عوامل ارزیابی سطح هوش، به سازمان‌ها در طراحی، خرید و پیاده‌سازی سیستم‌ها و نرم‌افزارها در راستای پشتیبانی تصمیم بهتر در تمامی سطوح کمک می‌نماید.
کلید واژگان:هوش تجاری، پشتیبانی تصمیم، سیستم‌های سازمانی، مدل ارزیابی
 

کلیدواژه‌ها

عنوان مقاله [English]

A Model for Assessing Business Intelligence level of Enterprise Systems

نویسندگان [English]

  • SaeedRouhan Rouhani 1
  • AhadZare Ravasan 2

1 Department of Industrial Engineering, Islamic Azad University, Firooz Kooh Branch, Firooz Kooh, Iran

2 ph.D Student of IT Management, AllamehTabataba’i University, Tehran, Iran

چکیده [English]

Most organizations still experience a lack of Business Intelligence (BI) in their decision making processes when implementing enterprise systems, such as Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), and Supply Chain Management (SCM). Consequently, a model and techniques to evaluate and assess the intelligence-level of enterprise systems can improve decision support. This paper proposes an expert tool to evaluate the BI competencies of enterprise systems, and combines a comprehensive review of recent literature with statistical methods for factor analysis. A statistical analysis has identified six factors for the evaluation model: ‘‘Analytical and Intelligent Decision-support’’, ‘‘Providing Related Experimentation and Integration with Environmental Information’’, ‘‘Optimization and Recommended Model’’, ‘‘Reasoning’’, ‘‘Enhanced Decision-making Tools’’, and finally, ‘‘Stakeholder Satisfaction’’.  Enterprises can use this approach to evaluate, select, and buy software and systems that provide better decision support for their organizational environment, enabling them to achieve competitive advantage.

کلیدواژه‌ها [English]

  • : Business Intelligence
  • Decision making support
  • Enterprise Systems
  • Assessment Model
مراجع
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  2. Azadivar, F., Truong, T., & Jiao, Y. (2009). A decision support system for fisheries management using operations research and systems science approach. Expert Systems with Applications, 36(2), 2971-2978.
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  8. Cheng, H., Lu, Y. C., & Sheu, C. (2009). An ontology-based business intelligence application in a financial knowledge management system. Expert Systems with Applications, 36(2), 3614-3622.
  9. du Plessis, T., & du Toit, A. (2006). Knowledge management and legal practice. International journal of information management, 26(5), 360-371.
  10. Eckerson, W. W. (2010). Performance dashboards: measuring, monitoring, and managing your business: Wiley.
  11. Elbashir, M. Z., Collier, P. A., & Davern, M. J. (2008). Measuring the effects of business intelligence systems: The relationship between business process and organizational performance. International Journal of Accounting Information Systems, 9(3), 135-153.
  12. Evers, M. (2008). An analysis of the requirements for DSS on integrated river basin management. Management of Environmental Quality: An International Journal, 19(1), 37-53.
  13. Feng, Y. H., Teng, T. H., & Tan, A. H. (2009). Modelling situation awareness for Context-aware Decision Support. Expert Systems with Applications, 36(1), 455-463.
  14. Gao, S., & Xu, D. (2009). Conceptual modeling and development of an intelligent agent-assisted decision support system for anti-money laundering. Expert Systems with Applications, 36(2), 1493-1504.
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  20. Lee, C., Lau, H., Ho, G., & Ho, W. (2009). Design and development of agent-based procurement system to enhance business intelligence. Expert Systems with Applications, 36(1), 877-884.
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  29. Quinn, N. W. T. (2009). Environmental decision support system development for seasonal wetland salt management in a river basin subjected to water quality regulation. agricultural water management, 96(2), 247-254.
  30. Raggad, B. G. (1997). Decision support system: use IT or skip IT. Industrial Management & Data Systems, 97(2), 43-50.
  31. Reich, Y., & Kapeliuk, A. (2005). A framework for organizing the space of decision problems with application to solving subjective, context-dependent problems. Decision Support Systems, 41(1), 1-19.
  32. Ross, J. J., Dena , M. A., & Mahfouf, M. (2009). A hybrid hierarchical decision support system for cardiac surgical intensive care patients. Part II. Clinical implementation and evaluation. Artificial Intelligence in Medicine, 45(1), 53-62.
  33. Sen, C. G., Baracli, H., Sen, S., & Basligil, H. (2009). An integrated decision support system dealing with qualitative and quantitative objectives for enterprise software selection. Expert Systems with Applications, 36(3), 5272-5283.
  34. Shang, J., Tadikamalla, P. R., Kirsch, L. J., & Brown, L. (2008). A decision support system for managing inventory at GlaxoSmithKline. Decision Support Systems, 46(1), 1-13.
  35. Shi, Z., Huang, Y., He, Q., Xu, L., Liu, S., Qin, L., . . . Zhao, L. (2007). MSMiner--a developing platform for OLAP. Decision Support Systems, 42(4), 2016-2028.
  36. Tan, X., Yen, D. C., & Fang, X. (2003). Web warehousing: Web technology meets data warehousing. Technology in Society, 25(1), 131-148.
  37. Tsoukiàs, A. (2008). From decision theory to decision aiding methodology. European Journal of Operational Research, 187(1), 138-161.
  38. Wen, W., Chen, Y., & Pao, H. (2008). A mobile knowledge management decision support system for automatically conducting an electronic business. Knowledge-Based Systems, 21(7), 540-550.
  39. Xiaoshuan, Z., Zetian, F., Wengui, C., Dong, T., & Jian, Z. (2009). Applying evolutionary prototyping model in developing FIDSS: An intelligent decision support system for fish disease/health management. Expert Systems with Applications, 36(2), 3901-3913.
  40. Yang, I. (2008). Utility-based decision support system for schedule optimization. Decision Support Systems, 44(3), 595-605.
  41. Yu, L., Wang, S., & Lai, K. K. (2009). An intelligent-agent-based fuzzy group decision making model for financial multicriteria decision support: the case of credit scoring. European Journal of Operational Research, 195(3), 942-959.
  42. Zack, M. H. (2007). The role of decision support systems in an indeterminate world. Decision Support Systems, 43(4), 1664-1674.
  43. Zhan, J., Loh, H. T., & Liu, Y. (2009). Gather customer concerns from online product reviews-A text summarization approach. Expert Systems with Applications, 36(2), 2107-2115.

 

  1. Alter, S. (2004). A work system view of DSS in its fourth decade. Decision Support Systems, 38(3), 319-327.
  2. Azadivar, F., Truong, T., & Jiao, Y. (2009). A decision support system for fisheries management using operations research and systems science approach. Expert Systems with Applications, 36(2), 2971-2978.
  3. Bartlett, M. S. (1950). Test of significance in factor analysis. British Journal of Psychology, 3, 77-85.
  4. Berzal, F., Cubero, J. C., & Jiménez, A. (2009). The design and use of the TMiner component-based data mining framework. Expert Systems with Applications, 36(4), 7882-7887.
  5. Bolloju, N., Khalifa, M., & Turban, E. (2002). Integrating knowledge management into enterprise environments for the next generation decision support. Decision Support Systems, 33(2), 163-176.
  6. Bose, R. (2009). Advanced analytics: opportunities and challenges. Industrial Management & Data Systems, 109(2), 155-172.
  7. Bucher, T., Gericke, A., & Sigg, S. (2009). Process-centric business intelligence. Business Process Management Journal, 15(3), 408-429.
  8. Cheng, H., Lu, Y. C., & Sheu, C. (2009). An ontology-based business intelligence application in a financial knowledge management system. Expert Systems with Applications, 36(2), 3614-3622.
  9. du Plessis, T., & du Toit, A. (2006). Knowledge management and legal practice. International journal of information management, 26(5), 360-371.
  10. Eckerson, W. W. (2010). Performance dashboards: measuring, monitoring, and managing your business: Wiley.
  11. Elbashir, M. Z., Collier, P. A., & Davern, M. J. (2008). Measuring the effects of business intelligence systems: The relationship between business process and organizational performance. International Journal of Accounting Information Systems, 9(3), 135-153.
  12. Evers, M. (2008). An analysis of the requirements for DSS on integrated river basin management. Management of Environmental Quality: An International Journal, 19(1), 37-53.
  13. Feng, Y. H., Teng, T. H., & Tan, A. H. (2009). Modelling situation awareness for Context-aware Decision Support. Expert Systems with Applications, 36(1), 455-463.
  14. Gao, S., & Xu, D. (2009). Conceptual modeling and development of an intelligent agent-assisted decision support system for anti-money laundering. Expert Systems with Applications, 36(2), 1493-1504.
  15. Ghoshal, S., & Kim, S. K. (1986). Building effective intelligence systems for competitive advantage. Sloan Management Review, 28(1), 49-58.
  16. González, J. R., Pelta, D. A., & Masegosa, A. D. (2009). A framework for developing optimization-based decision support systems. Expert Systems with Applications, 36(3), 4581-4588.
  17. Gottschalk, P. (2006). Expert systems at stage IV of the knowledge management technology stage model: The case of police investigations. Expert Systems with Applications, 31(3), 617-628.
  18. Granebring, A., & Révay, P. (2007). Service-oriented architecture is a driver for daily decision support. Kybernetes, 36(5/6), 622-635.
  19. Jalonen, H., & Lönnqvist, A. (2009). Predictive business–fresh initiative or old wine in a new bottle. Management Decision, 47(10), 1595-1609.
  20. Lee, C., Lau, H., Ho, G., & Ho, W. (2009). Design and development of agent-based procurement system to enhance business intelligence. Expert Systems with Applications, 36(1), 877-884.
  21. Lin, Y. H., Tsai, K. M., Shiang, W. J., Kuo, T. C., & Tsai, C. H. (2009). Research on using ANP to establish a performance assessment model for business intelligence systems. Expert Systems with Applications, 36(2), 4135-4146.
  22. Lönnqvist, A., & Pirttimäki, V. (2006). The measurement of business intelligence. Information Systems Management, 23(1), 32-40.
  23. Marinoni, O., Higgins, A., Hajkowicz, S., & Collins, K. (2009). The Multiple Criteria Analysis Tool (MCAT): A new software tool to support environmental investment decision making. Environmental Modelling & Software, 24(2), 153-164.
  24. Nemati, H. R., Steiger, D. M., Iyer, L. S., & Herschel, R. T. (2002). Knowledge warehouse: an architectural integration of knowledge management, decision support, artificial intelligence and data warehousing. Decision Support Systems, 33(2), 143-161.
  25. Ozbayrak, M., & Bell, R. (2003). A knowledge-based decision support system for the management of parts and tools in FMS. Decision Support Systems, 35(4), 487-515.
  26. Petrini, M., & Pozzebon, M. (2008). What Role is “Business Intelligence” Playing in Developing Countries? Data mining applications for empowering knowledge societies, 241.
  27. Power, D. J. (2008). Understanding data-driven decision support systems. Information Systems Management, 25(2), 149-154.
  28. Power, D. J., & Sharda, R. (2007). Model-driven decision support systems: Concepts and research directions. Decision Support Systems, 43(3), 1044-1061.
  29. Quinn, N. W. T. (2009). Environmental decision support system development for seasonal wetland salt management in a river basin subjected to water quality regulation. agricultural water management, 96(2), 247-254.
  30. Raggad, B. G. (1997). Decision support system: use IT or skip IT. Industrial Management & Data Systems, 97(2), 43-50.
  31. Reich, Y., & Kapeliuk, A. (2005). A framework for organizing the space of decision problems with application to solving subjective, context-dependent problems. Decision Support Systems, 41(1), 1-19.
  32. Ross, J. J., Dena , M. A., & Mahfouf, M. (2009). A hybrid hierarchical decision support system for cardiac surgical intensive care patients. Part II. Clinical implementation and evaluation. Artificial Intelligence in Medicine, 45(1), 53-62.
  33. Sen, C. G., Baracli, H., Sen, S., & Basligil, H. (2009). An integrated decision support system dealing with qualitative and quantitative objectives for enterprise software selection. Expert Systems with Applications, 36(3), 5272-5283.
  34. Shang, J., Tadikamalla, P. R., Kirsch, L. J., & Brown, L. (2008). A decision support system for managing inventory at GlaxoSmithKline. Decision Support Systems, 46(1), 1-13.
  35. Shi, Z., Huang, Y., He, Q., Xu, L., Liu, S., Qin, L., . . . Zhao, L. (2007). MSMiner--a developing platform for OLAP. Decision Support Systems, 42(4), 2016-2028.
  36. Tan, X., Yen, D. C., & Fang, X. (2003). Web warehousing: Web technology meets data warehousing. Technology in Society, 25(1), 131-148.
  37. Tsoukiàs, A. (2008). From decision theory to decision aiding methodology. European Journal of Operational Research, 187(1), 138-161.
  38. Wen, W., Chen, Y., & Pao, H. (2008). A mobile knowledge management decision support system for automatically conducting an electronic business. Knowledge-Based Systems, 21(7), 540-550.
  39. Xiaoshuan, Z., Zetian, F., Wengui, C., Dong, T., & Jian, Z. (2009). Applying evolutionary prototyping model in developing FIDSS: An intelligent decision support system for fish disease/health management. Expert Systems with Applications, 36(2), 3901-3913.
  40. Yang, I. (2008). Utility-based decision support system for schedule optimization. Decision Support Systems, 44(3), 595-605.
  41. Yu, L., Wang, S., & Lai, K. K. (2009). An intelligent-agent-based fuzzy group decision making model for financial multicriteria decision support: the case of credit scoring. European Journal of Operational Research, 195(3), 942-959.
  42. Zack, M. H. (2007). The role of decision support systems in an indeterminate world. Decision Support Systems, 43(4), 1664-1674.
  43. Zhan, J., Loh, H. T., & Liu, Y. (2009). Gather customer concerns from online product reviews-A text summarization approach. Expert Systems with Applications, 36(2), 2107-2115.

 

  1. Alter, S. (2004). A work system view of DSS in its fourth decade. Decision Support Systems, 38(3), 319-327.
  2. Azadivar, F., Truong, T., & Jiao, Y. (2009). A decision support system for fisheries management using operations research and systems science approach. Expert Systems with Applications, 36(2), 2971-2978.
  3. Bartlett, M. S. (1950). Test of significance in factor analysis. British Journal of Psychology, 3, 77-85.
  4. Berzal, F., Cubero, J. C., & Jiménez, A. (2009). The design and use of the TMiner component-based data mining framework. Expert Systems with Applications, 36(4), 7882-7887.
  5. Bolloju, N., Khalifa, M., & Turban, E. (2002). Integrating knowledge management into enterprise environments for the next generation decision support. Decision Support Systems, 33(2), 163-176.
  6. Bose, R. (2009). Advanced analytics: opportunities and challenges. Industrial Management & Data Systems, 109(2), 155-172.
  7. Bucher, T., Gericke, A., & Sigg, S. (2009). Process-centric business intelligence. Business Process Management Journal, 15(3), 408-429.
  8. Cheng, H., Lu, Y. C., & Sheu, C. (2009). An ontology-based business intelligence application in a financial knowledge management system. Expert Systems with Applications, 36(2), 3614-3622.
  9. du Plessis, T., & du Toit, A. (2006). Knowledge management and legal practice. International journal of information management, 26(5), 360-371.
  10. Eckerson, W. W. (2010). Performance dashboards: measuring, monitoring, and managing your business: Wiley.
  11. Elbashir, M. Z., Collier, P. A., & Davern, M. J. (2008). Measuring the effects of business intelligence systems: The relationship between business process and organizational performance. International Journal of Accounting Information Systems, 9(3), 135-153.
  12. Evers, M. (2008). An analysis of the requirements for DSS on integrated river basin management. Management of Environmental Quality: An International Journal, 19(1), 37-53.
  13. Feng, Y. H., Teng, T. H., & Tan, A. H. (2009). Modelling situation awareness for Context-aware Decision Support. Expert Systems with Applications, 36(1), 455-463.
  14. Gao, S., & Xu, D. (2009). Conceptual modeling and development of an intelligent agent-assisted decision support system for anti-money laundering. Expert Systems with Applications, 36(2), 1493-1504.
  15. Ghoshal, S., & Kim, S. K. (1986). Building effective intelligence systems for competitive advantage. Sloan Management Review, 28(1), 49-58.
  16. González, J. R., Pelta, D. A., & Masegosa, A. D. (2009). A framework for developing optimization-based decision support systems. Expert Systems with Applications, 36(3), 4581-4588.
  17. Gottschalk, P. (2006). Expert systems at stage IV of the knowledge management technology stage model: The case of police investigations. Expert Systems with Applications, 31(3), 617-628.
  18. Granebring, A., & Révay, P. (2007). Service-oriented architecture is a driver for daily decision support. Kybernetes, 36(5/6), 622-635.
  19. Jalonen, H., & Lönnqvist, A. (2009). Predictive business–fresh initiative or old wine in a new bottle. Management Decision, 47(10), 1595-1609.
  20. Lee, C., Lau, H., Ho, G., & Ho, W. (2009). Design and development of agent-based procurement system to enhance business intelligence. Expert Systems with Applications, 36(1), 877-884.
  21. Lin, Y. H., Tsai, K. M., Shiang, W. J., Kuo, T. C., & Tsai, C. H. (2009). Research on using ANP to establish a performance assessment model for business intelligence systems. Expert Systems with Applications, 36(2), 4135-4146.
  22. Lönnqvist, A., & Pirttimäki, V. (2006). The measurement of business intelligence. Information Systems Management, 23(1), 32-40.
  23. Marinoni, O., Higgins, A., Hajkowicz, S., & Collins, K. (2009). The Multiple Criteria Analysis Tool (MCAT): A new software tool to support environmental investment decision making. Environmental Modelling & Software, 24(2), 153-164.
  24. Nemati, H. R., Steiger, D. M., Iyer, L. S., & Herschel, R. T. (2002). Knowledge warehouse: an architectural integration of knowledge management, decision support, artificial intelligence and data warehousing. Decision Support Systems, 33(2), 143-161.
  25. Ozbayrak, M., & Bell, R. (2003). A knowledge-based decision support system for the management of parts and tools in FMS. Decision Support Systems, 35(4), 487-515.
  26. Petrini, M., & Pozzebon, M. (2008). What Role is “Business Intelligence” Playing in Developing Countries? Data mining applications for empowering knowledge societies, 241.
  27. Power, D. J. (2008). Understanding data-driven decision support systems. Information Systems Management, 25(2), 149-154.
  28. Power, D. J., & Sharda, R. (2007). Model-driven decision support systems: Concepts and research directions. Decision Support Systems, 43(3), 1044-1061.
  29. Quinn, N. W. T. (2009). Environmental decision support system development for seasonal wetland salt management in a river basin subjected to water quality regulation. agricultural water management, 96(2), 247-254.
  30. Raggad, B. G. (1997). Decision support system: use IT or skip IT. Industrial Management & Data Systems, 97(2), 43-50.
  31. Reich, Y., & Kapeliuk, A. (2005). A framework for organizing the space of decision problems with application to solving subjective, context-dependent problems. Decision Support Systems, 41(1), 1-19.
  32. Ross, J. J., Dena , M. A., & Mahfouf, M. (2009). A hybrid hierarchical decision support system for cardiac surgical intensive care patients. Part II. Clinical implementation and evaluation. Artificial Intelligence in Medicine, 45(1), 53-62.
  33. Sen, C. G., Baracli, H., Sen, S., & Basligil, H. (2009). An integrated decision support system dealing with qualitative and quantitative objectives for enterprise software selection. Expert Systems with Applications, 36(3), 5272-5283.
  34. Shang, J., Tadikamalla, P. R., Kirsch, L. J., & Brown, L. (2008). A decision support system for managing inventory at GlaxoSmithKline. Decision Support Systems, 46(1), 1-13.
  35. Shi, Z., Huang, Y., He, Q., Xu, L., Liu, S., Qin, L., . . . Zhao, L. (2007). MSMiner--a developing platform for OLAP. Decision Support Systems, 42(4), 2016-2028.
  36. Tan, X., Yen, D. C., & Fang, X. (2003). Web warehousing: Web technology meets data warehousing. Technology in Society, 25(1), 131-148.
  37. Tsoukiàs, A. (2008). From decision theory to decision aiding methodology. European Journal of Operational Research, 187(1), 138-161.
  38. Wen, W., Chen, Y., & Pao, H. (2008). A mobile knowledge management decision support system for automatically conducting an electronic business. Knowledge-Based Systems, 21(7), 540-550.
  39. Xiaoshuan, Z., Zetian, F., Wengui, C., Dong, T., & Jian, Z. (2009). Applying evolutionary prototyping model in developing FIDSS: An intelligent decision support system for fish disease/health management. Expert Systems with Applications, 36(2), 3901-3913.
  40. Yang, I. (2008). Utility-based decision support system for schedule optimization. Decision Support Systems, 44(3), 595-605.
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مطالعات مدیریت کسب و کار هوشمند
دوره 1، شماره 2 - شماره پیاپی 2
اسفند 1391
صفحه 105-121
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سابقه مقاله
  • تاریخ دریافت: 12 مهر 1391
  • تاریخ بازنگری: 10 تیر 1394
  • تاریخ پذیرش: 12 دی 1391
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